In the field of speech recognition, phrase spotting (also known as “word spotting” or “keyword spotting”) refers to the task of detecting the utterance of a target word or phrase within an acoustic input signal. In certain use cases, such as voice-based trigger scenarios, a phrase spotting system (running on, e.g., a smartphone or tablet) can perform phrase spotting on a continuous basis as it listens to sounds in its environment. If the phrase spotting system “spots” the target phrase (i.e., determines that the phrase has been spoken), the phrase spotting system can cause its host device (or another system/device) to take an action, such as processing a verbal command immediately following the target phrase, invoking an application, or the like.
One problem with performing phrase spotting on a continuous basis is that, due to environmental (i.e., background) noise, the phrase spotting system will likely generate a number of false accepts over a period of time. As known in the art, a “false accept” occurs when the phrase spotting system detects that the target phrase has been uttered when, in fact, it has not. In contrast, a “false reject” occurs when the phrase spotting system determines that the target phrase has not been uttered when, in fact, it has. If these false accepts occur frequently enough, the usability of the system can be impacted. Accordingly, it would be desirable to have improved phrase spotting techniques that address the foregoing and other similar issues.